Moraes, Alice Gallo de

Critically ill patients presenting with acute on chronic liver failure (ACLF) represent a particularly vulnerable population due to various considerations surrounding the syndrome definition, lack of robust prospective evaluation of outcomes, and allocation of resources such as organs for transplantation. Ninety-day mortality related to ACLF is high and patients who do leave the hospital are frequently readmitted. Artificial intelligence (AI), which encompasses various classical and modern machine learning techniques, natural language processing, and other methods of predictive, prognostic, probabilistic, and simulation modeling, has emerged as an effective tool in various areas of healthcare. These methods are now being leveraged to potentially minimize physician and provider cognitive load and impact both short-term and long-term patient outcomes. However, the enthusiasm is tempered by ethical considerations and a current lack of proven benefits. In addition to prognostic applications, AI models can likely help improve the understanding of various mechanisms of morbidity and mortality in ACLF. Their overall impact on patient-centered outcomes and countless other aspects of patient care remains unclear. In this review, we discuss various AI approaches being utilized in healthcare and discuss the recent and expected future impact of AI on patients with ACLF through prognostic modeling and AI-based approaches.

Patients with cirrhosis frequently require admission to the intensive care unit as complications arise in the course of their disease. These admissions are associated with high short- and long-term morbidity and mortality. Thus, understanding and characterizing complications and unique needs of patients with cirrhosis and acute-on-chronic liver failure helps providers identify appropriate level of care and evidence-based treatments. While there is no widely accepted critical care admission criteria for patients with cirrhosis, the presence of organ failure and primary or nosocomial infections are associated with particularly high in-hospital mortality. Optimal management of patients with cirrhosis in the critical care setting requires a system-based approach that acknowledges deviations from canonical pathophysiology. In this review, we discuss appropriate considerations and evidence-based practices for the general care of patients with cirrhosis and critical illness.